Temporal activity detection in untrimmed videos aims to localize the action instances in time and recognize their categories. This task is considerably more complicated than action recognition which merely seeks to classify the categories of trimmed video clips. Fig. REF  shows an example of temporal activity detection in an untrimmed video recorded in a stadium. The first row demonstrates the detection of action "long jump" in temporal domain where the start and end time of the action are localized. The goal is to only detect the actions of interest, i.e., actions that belong to a predefined set of action classes. The temporal intervals of other activities that do not belong to this set of actions are called temporal background. For example, the segments right before or right after action "long jump" may belong to other diverse activities such as crowd cheering in the stadium. In some cases, the frames right before or right after an action are visually very similar to the start or end of the action which makes the localization of action intervals very challenging. Another challenge (as shown in the second row of Fig. REF ) is that action instances may occur at any time of the video and have various duration, lasting from less than a second to several minutes [1]}.
